FUNAAB Robotic Ranching System
Robotic ranching represents the integration of AI and specifically, advanced robotic technologies into livestock and ranching management. It promotes a technological procedure, more efficient, sustainable, and data‐driven approach to managing livestock operations by automating tasks such as herding, feeding, monitoring, and even aspects of animal care. This project presents the use of an invisible wheeled-service robot to feed cattle autonomously and generate real‐time data with precise control in order to ensure that the cattle receive timely and accurate concentrated feed. The noiseless oval-shaped Internet of Things (IoT) enabled robot will move along its lane at a fixed time twice a day to autonomously dispense feed to the cattle and send its data details to the backend. This technological advancement in cattle production will enable more informed decisions about resource use such as optimized feed distribution, efficient water use, and targeted interventions to prevent disease. This data-driven approach will not only minimize waste but would also help to reduce the environmental footprint of livestock operations. The continuous monitoring provided by robotic systems supports precision management in ranching. The real-time data that would be gathered will be further analyzed to refine practices, adjust feeding regimens, and improve overall herd management strategies. The on-going project is an integration of robotics and big data ultimately will lead to more effective and responsive livestock management. Thus, robotic ranching will promote a shift toward more automated, precise, and sustainable livestock management. It leverages technology to reduce labour dependency, improve animal care through continuous monitoring, and optimize resource use, ultimately paving the way for a more resilient and efficient future in ranching.
Project Team
A dedicated group of Professors, Doctors, Researchers, Engineers, and Agriculturalists from FUNAAB.
Prof. Olufunke Rebecca Vincent
Department Of Cybersecurity and Data Science
Prof. Olufunke R. Vincent is a Professor of Artificial Intelligence at the Federal University of Agriculture, Abeokuta (FUNAAB). She specializes in Artificial Intelligence, Data Science, and Image and Vision processing, with a strong focus on the applications of AI in agriculture and society.
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Prof. B. O. Oluwatosin
IFSERAR Department
Prof. (Mrs.) Bamidele Omonuwa Oluwatosin is a Professor at the Federal University of Agriculture, Abeokuta (FUNAAB), Nigeria, specializing in Ruminant Animal Production. She has served as Director of IFSERAR and Visiting Scientist at ILRI, Burkina Faso, and is a Fellow of the College of Animal Scientists of Nigeria (FCASN).
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Dr. A. T. Oyelami
Mechatronics Department
Dr. A.T. Oyelami holds a Ph.D Degree in Mechanical Engineering with a bias for Design & Production / Computer Aided Engineering. He is registered with the Council for the Regulation of Engineering in Nigeria (COREN) and a Corporate Member of the Nigerian Society of Engineers.
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Prof. (Engr.) Adebayo Abayomi-Ali
Computer Science Department
Engr. Abayomi-Alli Adebayo is a Lecturer at the Federal University of Agriculture, Abeokuta (FUNAAB), Nigeria. He holds a B.Tech. in Computer Engineering, an M.Sc. and Ph.D. in Computer Science, and is a COREN Chartered Engineer and Certified IT Practitioner (C.itp). His research interests include pattern recognition, machine learning, and microprocessor-based systems.
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Mr Dauda Wisdom Daniel
Computer Science Department
Daniel Dauda Wisdom is a researcher at Federal University of Agriculture Abeokuta (FUNAAB). A professional in the field of Cybersecurity. He holds a Bachelor of Science degree (B.Sc) in Information Technology, Master of Science degree (M.Sc) in Computer Science, Professional Diploma in Education. He is also a Certified Ethical Hacker (CEH) from EC Council UK.
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